Walmart Data
The scenario is the number of Wal-Mart stores for each year from 2003 - 2010. The data is (2003, 4906), (2004, 5289), (2005, 6141), (2006, 6779), (2007, 7262), (2008, 7720), (2009, 8416), (2010, 8970). Each of these graphs is plotted with these points. With this plot I need to formulate a curve of best fit using the correlation coefficient.
This graph is about the number of Walmart employees. The X-axis is the Time ( years after 2002). The Y-axis is the number of Walmart employees (in thousands). The equation is Y= 586.94x + 3120.3. The graph stays on a linear line going up to 10000. This graph has a correlation coefficient: Interval of r: -1 ≤ r ≤ 1. The graph has strong linear correlation because the value is close to one. When you square root 0.9952 you get r = 0.9975. …show more content…
This graph is the number of employees at Wal-mart.
The X-axis is the year after 2002 which is the time. The Y-axis is the number of Wal-mart employees but counted in the thousands. The equation of this graph is y= -5.6607x^2 + 660.53x + 2910.8. This graph stays in a linear line going up. This graph has a correlation coefficient: interval of r: -1 ≤ r ≤ 1. The graph has a strong linear correlation because the value is closest to one. When you take R^2 = 0.9956 and square root it you get r = 0.9977. Which is greater than graph one.
This graph is the number of employees at Wal-mart. The X-axis represents the years after 2002. The Y-axis represents the number of Wal-mart employees in thousands. The graph equation is y= 0.7854x^3 - 20.975x^2 + 752.81x + 2742.4. When the points are plotted its a linear line. This graph has a correlation coefficient: interval of r: -1 ≤ r ≤ 1. The graph has a strong linear correlation because the value is closest to one. When you take R^2 = 0.9956 and square root it you get r = 0.9977. Which is equal to the second graph. All three of these graph have to has a strong linear correlation. The best graph to chose is graph 2 or graph 3 because both is r =
0.9977.
This graph is about the number of Walmart employees. The X-axis is the Time ( years after 2002). The Y-axis is the number of Walmart employees (in thousands). The equation is Y= 586.94x + 3120.3. The graph stays on a linear line going up to 10000. This graph has a correlation coefficient: Interval of r: -1 ≤ r ≤ 1. The graph has strong linear correlation because the value is close to one. When you square root 0.9952 you get r = 0.9975. …show more content…
This graph is the number of employees at Wal-mart.
The X-axis is the year after 2002 which is the time. The Y-axis is the number of Wal-mart employees but counted in the thousands. The equation of this graph is y= -5.6607x^2 + 660.53x + 2910.8. This graph stays in a linear line going up. This graph has a correlation coefficient: interval of r: -1 ≤ r ≤ 1. The graph has a strong linear correlation because the value is closest to one. When you take R^2 = 0.9956 and square root it you get r = 0.9977. Which is greater than graph one.
This graph is the number of employees at Wal-mart. The X-axis represents the years after 2002. The Y-axis represents the number of Wal-mart employees in thousands. The graph equation is y= 0.7854x^3 - 20.975x^2 + 752.81x + 2742.4. When the points are plotted its a linear line. This graph has a correlation coefficient: interval of r: -1 ≤ r ≤ 1. The graph has a strong linear correlation because the value is closest to one. When you take R^2 = 0.9956 and square root it you get r = 0.9977. Which is equal to the second graph. All three of these graph have to has a strong linear correlation. The best graph to chose is graph 2 or graph 3 because both is r =
0.9977.